1. Introduction to Proteomics
Phil Charles
CCMP

2. Overview of Talk Overview of proteomics as a concept
Techniques discussion
2D Gels and experimental design paradigms
Proteomics mass spectrometry
Identification
Quantitation

3. Proteomics is the study of the overall state of an organism’s temporal protein composition
The biological state of the proteome is encoded in
The relative abundance of currently expressed proteins (and their isoform)
Their localisation relative to cellular (or extracellular) structures
Their interaction partner molecules and substrates
Their current post-translational modification state
Their folded structures …

4. A Different View on Life
Genome  Transcriptome  Proteome … Phenotype
Different levels of biological complexity
More layers of regulation and control
Increased heterogeneity of samples

5. Why consider Proteomics?
Orthogonal verification of gene activity.
Observe biological state after more levels of regulation and control – closer to phenotypic outcome.
Observe proteomes of extracellular locations – blood plasma/serum, urine etc.

6. Proteomics Classical biochemistry Two-dimensional gels (2DGE)
Mass spectrometry
Computational analysis

7. Methods in Proteomics Separation Identification Quantitation Gels
Immunochemistry
Chromatography
Identification
Mass spectrometry
Quantitation
All of the above

8. Identification vs Quantitation
What’s there? How much of it is there?
How sure are you about the ID?
How sure are you about the abundance?
Not there versus not detectable

9. 2DGE Separate proteins by isoelectric point, then by mass
Visualise with silver staining or coomassie
Use CyDyes to label samples so they can be run together on the same gel
Appl Microbiol Biotechnol October; 76(6): 1223–1243.

10. Quantitation Experimental Paradigm - Labelling
Label samples in such a way as to not affect subsequent processing but allow differentiation in final analysis. Examples:
Fluorescent dyes (2DGE)
SILAC amino acid labels (MS)
Isobaric mass tags (MS/ MS)
Process multiple samples simultaneously, differentiate only in final analysis on basis of label.
Avoid some proportion of technical variance
Best to worst (for avoiding technical variance):
Labelling in vivo
Labelling protein mixture
Labelling peptide digestion mixture

11. Aline Chrétien, Edouard Delaive, Marc Dieu, Catherine Demazy, Noëlle Ninane, Martine Raes, Olivier Toussaint
Upregulation of annexin A2 in H2O2-induced premature senescence as evidenced by 2D-DIGE proteome analysis
Experimental Gerontology, Volume 43, Issue 4, April 2008, Pages 353–359

12. Quantitation Experimental Paradigm – Normalising to standard
Combine each sample (labelled with one label) with a representative standard (labelled with another label).
Perform analysis
For each protein in each run, normalise observed abundance in labelled sample to observed abundance in labelled standard.

13. Statistical Analysis Normalised Abundance Normalised Abundance

14. Mass Spectrometry
Mass Spectrometry is a technique for the detection and resolution of a sample of ions by their mass-to-charge ratio - represented by m/z where m is the mass in Daltons and z is the charge. ’

15. Proteomic Mass Spectrometry
Classical biochemistry techniques and 2DGE are, in general, ‘top-down proteomics’ – identify and quantify whole proteins.
Most modern proteomic MS is ‘bottom-up’

16. Shotgun/’bottom-up’ proteomics
Separation
SDS-PAGE
Antibody-based approaches
LNDLEEALQQACEDLAR
N KLNDLEEALQQAK
Digestion
Separation
SCX
High pH RP LC
Low pH RP LC
Analysis
MS-MS/
Tandem MS
LNDLEEALQQAKEDLAR
NKLNDLEEALQQAK
NVQDAIADAEQR
SKEEAEALYHSK
SLVGLGGTK
TAAENDFVTLK
TAAENDFVTLKK
TSQNSELNNMQDLVEDYK
TSQNSELNNMQDLVEDYKK
VDLLNQEIEFLK
YEELQVTVGR
YLDGLTAER
ADLEMQIESLTEELAYLK
ADLEMQIESLTEELAYLKK
AETECQNTEYQQLLDIK
Peptide IDs
+ Quantitation
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
IPI:IPI
Observed Proteins
+ Quantitation
Proteins
Peptides

17. Tandem Mass Spectrometry
Intensity
m/z
Mass Analyser + Detector
Mass Spectrum
Sample
Tandem Mass Spectrum
MS/MS spectrum
m/z
Intensity
Mass Analyser + Detector

18. Identification by MS/MS
Mass Analyser + Detector
Search fragment spectrum against a database of protein sequences. For each sequence, digest into peptides, generate an expected fragment ion spectrum, and match to observed spectrum
m/z
Intensity ?
m/z
Intensity
IITHPNFNGNTLDNDIMLIK

19. Identification by MS/MS
There are multiple commonly used MS/MS fragment spectra search engines, including:
Mascot
Sequest
OMSSA
X!Tandem
MS Amanda
Andromeda
ProteinPilot

20. A brief overview of Mass Spectrometric quantitation
Please feel free to stop me and ask questions!

21. Tandem Mass Spectrometry
Intensity
m/z
Mass Analyser + Detector
Mass Spectrum
Sample
Tandem Mass Spectrum
MS/MS spectrum
m/z
Intensity
Mass Analyser + Detector

22. Select Peptide Ions
Low pH Reverse Phase LC
‘Survey Scan’/
‘MS1’/
‘MS Scan’
Fragmentation
CID
Also ETD,
PQD,HCD
‘Fragment Ions Scan’/
‘MS2’/
‘MS/MS Scan’
Data-Dependent Acquisition (DDA)
time

23. Intensity
Retention Time
m/z

24. Intensity
Retention Time
m/z
Intensity
m/z

25. Peptide Isotopomer Distribution
This is all 1 peptide
Intensity
m/z
Think of it as a frequency distribution based on a probability function.
The relative intensity of each peak is the relative chance of a single peptide molecule having that m/z
1/charge (z)

26. Intensity
Retention Time
m/z
Intensity
m/z

27. IITHPNFNGNTLDNDIMLIK
Intensity
Intensity
m/z
m/z
Intensity
Retention Time
IITHPNFNGNTLDNDIMLIK
m/z

28. Quantitation Labelling Strategies
MS-based strategies
In-vivo labelling (compare peak pairs)
SILAC, 15N, 18O, 2H
MS/MS-based strategies
Isobaric Tags
iTRAQ, TMT

29. Intensity
Retention Time
m/z
Intensity
m/z
m/z
Intensity

30. Intensity
Retention Time
m/z
Intensity
m/z
Intensity
m/z

31. Isobaric Tag Labels e.g. iTRAQ, TMT

32. IITHPNFNGNTLDNDIMLIK
Intensity
Intensity
m/z
m/z
Intensity
Retention Time
IITHPNFNGNTLDNDIMLIK
m/z

33. Intensity
Retention Time
m/z
Intensity
m/z
Intensity
m/z

34. Intensity
Retention Time
m/z

35. MS quantitation - peak pair comparison
Intensity
Retention Time
m/z
MS quantitation - peak pair comparison

36. Intensity
Retention Time
m/z

37. Intensity
Retention Time
m/z

38. Intensity
Retention Time
m/z ID ID ID ID ID

39. Identification vs Quantitation
What’s there? How much of it is there?
How sure are you about the ID?
How sure are you about the abundance?
Not there versus not detectable

40. Quantitation Software
MaxQuant
Progenesis LC-MS
ABI Peaks
Thermo ProteomeDiscoverer
+ bespoke and specific tools

41. The Oxford Central Proteomics Facility
CCMP/CPF – Kessler Lab – WTCHG
CPF - Ben Thomas – Dunn School
Computational Biology Research group - WIMM

44. Thank you for your attention
Please feel free to ask questions